Dynamic pricing systems and methods

ABSTRACT

Example dynamic pricing systems and methods are described. A system can comprise one or more programs comprising instructions to receive a request from a graphical user interface of a mobile device of a user for a price of one or more items; receiving an indication of an occurrence of a first event unrelated to a particular customer, wherein the first event is related to the one or more items; receive an indication of an occurrence of a second event unrelated to a particular customer, wherein the second event is related to the one or more items; access data regarding the first event and the second event; determine whether to adjust the price associated with the one or more items based on the data regarding the first event and the second event; responsive to determining to adjust the price associated with the one or more items, determine a new price for the one or more items based on the first event, the second event, and previous user behavior comprising at least one of user loyalty, user returns, or user interests of the user; generate a search listing comprising the one or more items responsive to the request of the user based on the price, as adjusted, of the one or more items in the search listing; when it is determined that a price adjustment is not required for the one or more items, displaying the price without adjustment of the one or more items in response to the request of the user; and facilitating displaying, to the graphical user interface of the mobile device, the final search listing in response to the request of the user. Other embodiments are disclosed herein.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a divisional of U.S. patent application Ser. No.14/266,519, filed Apr. 30, 2014, which is incorporated herein byreference in its entirety.

TECHNICAL FIELD

The present disclosure relates to systems and methods that supportdynamic pricing of one or more items

BACKGROUND

Dynamic pricing, or the adjustment of item pricing by retailers, is animportant part of today's competitive retail environment. Contemporaryprice adjustment systems in use today mostly rely on periodic priceadjustments that need to be done manually by designated personnel, andthis process can be time-consuming and laborious. Furthermore,contemporary systems adjust pricing mostly based on competitor priceadjustments. In reality, there are numerous factors that might affectpricing in real-time.

BRIEF DESCRIPTION OF THE DRAWINGS

Non-limiting and non-exhaustive embodiments of the present disclosureare described with reference to the following figures, wherein likereference numerals refer to like parts throughout the various figuresunless otherwise specified.

FIG. 1 is a block diagram depicting an environment within which anexample embodiment may be implemented.

FIG. 2 is a block diagram depicting an embodiment of a structure formanaging events in a dynamic pricing system.

FIG. 3 is a block diagram depicting an example embodiment of a dynamicpricing manager.

FIG. 4 represents a flow diagram depicting an embodiment of a method formonitoring and capturing event data.

FIG. 5 represents a flow diagram depicting an embodiment of a method fordetermining whether to adjust the price of an item.

FIG. 6 represents a flow diagram depicting an embodiment of a method forgenerating a search listing in response to a query.

FIG. 7 represents a flow diagram depicting an embodiment of a dynamicpricing algorithm.

FIG. 8 represents an example of representative variables associated withthe dynamic pricing algorithm.

FIG. 9 represents an example of representative variables associated withthe dynamic pricing algorithm with specific items and associated itemcategories.

DESCRIPTION OF EXAMPLES OF EMBODIMENTS

In one embodiment, a system can comprise one or more processors; andmemory storing one or more programs to be executed by the one or moreprocessors, the one or more programs comprising instructions for:receive a request from a graphical user interface of a mobile device ofa user for a price of one or more items; receive an indication of anoccurrence of a first event unrelated to a particular customer, whereinthe first event is related to the one or more items; receive anindication of an occurrence of a second event unrelated to a particularcustomer, wherein the second event is related to the one or more items;access data regarding the first event and the second event; determinewhether to adjust the price associated with the one or more items basedon the data regarding the first event and the second event; responsiveto determining to adjust the price associated with the one or moreitems, determine a new price for the one or more items based on thefirst event, the second event, and previous user behavior comprising atleast one of user loyalty, user returns, or user interests of the user;generate a search listing comprising the one or more items responsive tothe request of the user based on the price, as adjusted, of the one ormore items in the search listing; when it is determined that a priceadjustment is not required for the one or more items, displaying theprice without adjustment of the one or more items in response to therequest of the user; and facilitating displaying, to the graphical userinterface of the mobile device, the final search listing in response tothe request of the user.

In one embodiment, a method can comprise: receiving, with a computersystem using one or more processors, a request from a graphical userinterface of a mobile device of a user for a price of one or more items;receiving, with the computer system, an indication of an occurrence of afirst event unrelated to a particular customer, wherein the first eventis related to the one or more items; receiving, with the computersystem, an indication of an occurrence of a second event unrelated to aparticular customer, wherein the second event is related to the one ormore items; accessing, with the computer system, data regarding thefirst event and the second event; determining, with the computer system,whether to adjust the price associated with the one or more items basedon the data regarding the first event and the second event; responsiveto determining to adjust the price associated with the one or moreitems, determining, with the computer system, a new price for the one ormore items based on the first event, the second event, and previous userbehavior comprising at least one of user loyalty, user returns, or userinterests of the user; generating, with the computer system, a searchlisting comprising the one or more items responsive to the request ofthe user based on the price, as adjusted, of the one or more items inthe search listing; when it is determined that a price adjustment is notrequired for the one or more items, displaying, with the computersystem, the price without adjustment of the one or more items inresponse to the request of the user; and facilitating displaying, withthe computer system, to the graphical user interface of the mobiledevice, the final search listing in response to the request of the user.

In the following description, reference is made to the accompanyingdrawings that form a part thereof, and in which is shown by way ofillustration specific exemplary embodiments in which the disclosure maybe practiced. These embodiments are described in sufficient detail toenable those skilled in the art to practice the concepts disclosedherein, and it is to be understood that modifications to the variousdisclosed embodiments may be made, and other embodiments may beutilized, without departing from the scope of the present disclosure.The following detailed description is, therefore, not to be taken in alimiting sense.

Reference throughout this specification to “one embodiment,” “anembodiment,” “one example,” or “an example” means that a particularfeature, structure, or characteristic described in connection with theembodiment or example is included in at least one embodiment of thepresent disclosure. Thus, appearances of the phrases “in oneembodiment,” “in an embodiment,” “one example,” or “an example” invarious places throughout this specification are not necessarily allreferring to the same embodiment or example. Furthermore, the particularfeatures, structures, databases, or characteristics may be combined inany suitable combinations and/or sub-combinations in one or moreembodiments or examples. In addition, it should be appreciated that thefigures provided herewith are for explanation purposes to personsordinarily skilled in the art and that the drawings are not necessarilydrawn to scale.

Embodiments in accordance with the present disclosure may be embodied asan apparatus, method, or computer program product. Accordingly, thepresent disclosure may take the form of an entirely hardware-comprisedembodiment, an entirely software-comprised embodiment (includingfirmware, resident software, micro-code, etc.), or an embodimentcombining software and hardware aspects that may all generally bereferred to herein as a “circuit,” “module,” or “system.” Furthermore,embodiments of the present disclosure may take the form of a computerprogram product embodied in any tangible medium of expression havingcomputer-usable program code embodied in the medium.

Any combination of one or more computer-usable or computer-readablemedia may be utilized. For example, a computer-readable medium mayinclude one or more of a portable computer diskette, a hard disk, arandom access memory (RAM) device, a read-only memory (ROM) device, anerasable programmable read-only memory (EPROM or Flash memory) device, aportable compact disc read-only memory (CDROM), an optical storagedevice, and a magnetic storage device. Computer program code forcarrying out operations of the present disclosure may be written in anycombination of one or more programming languages. Such code may becompiled from source code to computer-readable assembly language ormachine code suitable for the device or computer on which the code willbe executed.

Embodiments may also be implemented in cloud computing environments. Inthis description and the following claims, “cloud computing” may bedefined as a model for enabling ubiquitous, convenient, on-demandnetwork access to a shared pool of configurable computing resources(e.g., networks, servers, storage, applications, and services) that canbe rapidly provisioned via virtualization and released with minimalmanagement effort or service provider interaction and then scaledaccordingly. A cloud model can be composed of various characteristics(e.g., on-demand self-service, broad network access, resource pooling,rapid elasticity, and measured service), service models (e.g., Softwareas a Service (“SaaS”), Platform as a Service (“PaaS”), andInfrastructure as a Service (“IaaS”)), and deployment models (e.g.,private cloud, community cloud, public cloud, and hybrid cloud).

The flow diagrams and block diagrams in the attached figures illustratethe architecture, functionality, and operation of possibleimplementations of systems, methods, and computer program productsaccording to various embodiments of the present disclosure. In thisregard, each block in the flow diagrams or block diagrams may representa module, segment, or portion of code, which comprises one or moreexecutable instructions for implementing the specified logicalfunction(s). It will also be noted that each block of the block diagramsand/or flow diagrams, and combinations of blocks in the block diagramsand/or flow diagrams, may be implemented by special purposehardware-based systems that perform the specified functions or acts, orcombinations of special purpose hardware and computer instructions.These computer program instructions may also be stored in acomputer-readable medium that can direct a computer or otherprogrammable data processing apparatus to function in a particularmanner, such that the instructions stored in the computer-readablemedium produce an article of manufacture including instruction meanswhich implement the function/act specified in the flow diagram and/orblock diagram block or blocks.

The systems and methods described herein support dynamic pricingadjustment of items. In particular implementations, a dynamic,substantially real-time pricing system adjusts the pricing of retailitems based on one or more events. The pricing adjustments can beperformed automatically or manually, and the pricing system is capableof dynamically adjusting item pricing in substantially real time. Asused herein, dynamic pricing refers to the changing of item pricingbased on the occurrence of one or more events and not being limited tocompetitor pricing adjustments alone. For example, the introduction of anew model of an item by a manufacturer can be an event that causes thedescribed dynamic pricing systems and methods to adjust the price of anolder model of the item. In another example, the described systems andmethods can also be triggered by the proximity of a customer to aparticular store. Based on the browsing history of the customer, analert can be sent to the mobile device of the customer if the customeris in the proximity of a store that has the item of interest in stock.Information sent to the customer can include not only the storelocation, but also the current price of the item, and may include acoupon or other discount for the item.

FIG. 1 is a block diagram depicting an environment 100 within which anexample embodiment may be implemented. Environment 100 includes adynamic pricing manager 104 coupled to an event cloud 102. The eventcloud 102 stores multiple event adapters that identify the occurrence ofa variety of different events. The event cloud 102 may identify anynumber of different events and information, such as customer profileinformation, transaction history data, location information (e.g.,proximity to a physical store), geographic data, social media data, iteminformation, related products, items purchased, total purchase data,inventory levels, item markdowns, supply chain events, and the like.

In one embodiment of the system, events can be added or removed from thelist of events based on need, where the list of events need not berigidly predefined. Introduction or removal of factors associated withthe item determine addition or removal of a particular event. Forexample, if a product is sold exclusively by the vendor, the factor ofcompetitor price doesn't exist. But, if other online retailers startselling the item, then a new factor is introduced—competitor price—whichtriggers the addition of a competitor price event. In some embodiments,addition of the event leads to:

1. A merchandiser assigning a certain weight to the event, or

2. Allow the event to be populated with an initial value from apre-defined category list (dynamic).

As an example of dynamic population, an electronics category has apre-defined variable list from which the parameters are inherited forall items falling in the category. Taking the above example, if acompetitor price does not exist, a zero value is assigned to thecompetitor price parameter in the corresponding list for that item. Whenthe crawler program for competitor price initiates this new event, itassigns the pre-defined category parameter to the item and decreasesother parameters (e.g., round to a factor of 1 for all parameterweightings).

The dynamic pricing manager 104 further includes an event orchestrator106, a trend analyzer 108, a price optimizer 110 and item master andpricing systems 112. The event orchestrator 106 receives event changesfrom the event cloud 102 and triggers the price optimizer 110. The priceoptimizer 110 calculates the revised item price based on event changesreceived from the event orchestrator 106 and transmits back the revisedprice to the event orchestrator 106. In some situations, one or moreevents may occur that do not cause a revision in the price of an item.The price optimizer 110 also transmits the revised price to the itemmaster and pricing systems 112, where the price of the particular itemis updated if necessary, either automatically or manually, as often asrequired. The trend analyzer 108 analyzes historical trends of orderchanges based on multiple variables (for example, average profit, orderchange, inventory change, social buzz, competitor price change, page hitchanges, shipping cost changes, cost of goods changes, and promotionalevent changes) and input from the price optimizer 110. The trendanalyzer 108 is also able to modify these variables used to analyze thehistorical trends of order changes. In this sense, these variablesassociated with the trend analyzer 108 are self-correcting.

The dynamic pricing manager 104, and specifically the event orchestrator106, is further coupled to a data communication network 120, such as theInternet, and a cellular communication network 122. The eventorchestrator 106 can communicate with a mobile device 116, via thecellular communication network 122. The event orchestrator can alsocommunicate, via the data communication network 120, with a user device114 and a kiosk 118. The user device 114, mobile device 116 and kiosk118 represent interfaces that allow the dynamic pricing manager tointeract with a customer. Although one user device 114, one mobiledevice 116 and one kiosk 118 are shown in FIG. 1, particular embodimentsmay include any number of user devices, mobile devices and kioskscommunicating with the dynamic pricing manager 104, specifically theevent orchestrator 106, through the data communication network 120and/or the cellular communication network 122. In some embodiments, thekiosk 118 is an in-store kiosk including a computing device that allowsusers to access item pricing and other information while shopping in thestore.

FIG. 2 is a block diagram depicting an embodiment of a structure formanaging events in the dynamic pricing system. In this embodiment, theevent cloud 102 receives inputs from multiple information sourcesincluding a kiosk 118, a mobile device 116, a point-of-sale terminal202, the world-wide web 204, a call center 206 and email 208.Collectively these information sources connect to the event cloud 102.Although one kiosk 118, one mobile device 116, one point-of-saleterminal 202, one call center 206 and one email source 208 are shown inFIG. 2, particular embodiments may include any number of kiosks, mobiledevices, point-of-sale terminals, call centers and email sourcescommunicating with the event cloud 102. The event cloud transmits thedata received from kiosk 118, mobile device 116, the point-of-saleterminal 202, the world-wide web 204, the call center 206 and the emailsource 208 to an information bus 210. The event cloud 102 also receivesdata from the information bus 210. The information bus 210 is alsoconnected to multiple other data sources including customer item data212, stores 214, store support center 216, online stores 218, ordermanagement systems 220, marketing systems 222, and warehouse systems224, that send additional information to and receive additional datafrom the information bus 210. Examples of the different types of datagenerated and communicated to and from the information bus 210 by eachof the illustrated systems or devices connected to the information busare as follows.

Kiosk 118—Example Data: number of item views, number of orders placedfor that item.

Mobile device 116—Example Data: number of item views, number of ordersplaced for the item, numerical distance—store proximity.

Point-of-sale terminal 202—Example Data: number of orders for the item,a number of returns for the item.

Web 204—Example Data: Social buzz like Facebook likes or dislikes,Competitor price.

Call center 206—Example Data: number of call-in orders for the item oritem returns.

Email 208—Example Data: number of item recommendations by email reviewsfor the item.

Customer item data 212—Example Data: Profit margin, Price updates,number of days for item expiry on site for the item.

Stores 214—Example Data: percentage increase/decrease in storeinventory.

Store support center 216—Example Data: store returns.

Online stores 218—Example Data: number of item views or category views,addition to carts, cart abandonments.

Order management systems 220—Example Data: number of orders for theitem, inventory changes for the item.

Marketing systems 222—Example Data: Email views and reviews of the itemof marketing campaigns.

Warehouse systems 224—Example Data: item movement to distributioncenters which forecasts changes to inventory.

FIG. 3 is a block diagram depicting an embodiment of a dynamic pricingmanager 104. Dynamic pricing manager 104 includes a communication module302, a processor 304, and a memory 306. Communication module 302 allowsdynamic pricing manager 104 to communicate with other systems such asevent cloud 102, user device 114 and kiosk 118 via data communicationnetwork 120, and mobile device 116 via cellular communication network122. Processor 304 executes various instructions to implement thefunctionality provided by dynamic pricing manager 104. Memory 306 storesthese instructions as well as other data used by processor 304 and othermodules contained in dynamic pricing manager 104.

Dynamic pricing manager 104 also includes a trend analysis manager 308that analyzes historical trends of order changes based on multiplevariables and changes multiple parameters if necessary. The differenttypes of data received from any combination of kiosk 118, mobile device116, point-of-sale terminal 202, web 204, call center 206, email 208,customer item data 212, stores 214, store support center 216, onlinestores 218, order management systems 220, marketing systems 222 andwarehouse systems 224 are considered as multiple variables. For example,drop-in item orders or customer views—online/kiosk—would trigger afactored increase in parameter values for positive parameters and afactored decrease in parameter values that would result a correspondingprice decrease for the item.

A price analysis manager 310 performs the computation to determinerevised item price and transmits the revised item price to the eventmanager 312. The event manager 312 is also performs the function ofidentifying events from event cloud 102 and subsequently triggering theprice analysis manager 310 to perform computations for revised itempricing. The display generator 314 generates display data to bepresented to a user or to be stored for future presentation to the user.For example, the display generator can generate a search results listingfor presentation to the user. The user interface manager 316 generatesuser interface components that allow the dynamic pricing manager 104 andother components of the system to present user interface components toone or more users.

FIG. 4 represents a flow diagram depicting an embodiment of a method 400for monitoring and capturing event data. Initially, the system receivesan indication of an occurrence of a first event at 402, for example aseasonal event. The system then stores the data associated with thefirst event at 404. The system then receives an indication of anoccurrence of a second event at 406, for example social buzz related toa particular item. The system then stores the data associated with thesecond event at 408. Based on the first event and the second event, thesystem determines whether to adjust a price associated with a particularitem at 410. If necessary, the system determines a new price for theparticular item based on the first event and the second event at 412.The weighted seed algorithm discussed below is a specific example ofdetermining whether to adjust an item price based on one or more events.

FIG. 5 represents a flow diagram depicting an embodiment of a method 500for determining whether to adjust the price of an item. For example, acustomer may request the price of a seasonal item at some point.Initially, the system receives a request for an item price at 502. Thesystem then accesses previously stored event data for one or multipleevents at 504. Then, the system determines whether a price adjustment isrequired at 506. If a price adjustment is required, the systemdetermines a new price associated with a particular item at 508, adjuststhe price of the particular item at 510, and then communicates the priceof the particular item to the source of the price request at 512. If itis determined that a price adjustment is not required at 506, the systemdirectly communicates the price of the particular item to the source ofthe price request at 512.

FIG. 6 represents a flow diagram depicting an embodiment of a method 600for generating a search listing in response to a query. In thisembodiment, the system receives a query for information related to oneor more items at 602. The system then identifies appropriate items todisplay in response to the query at 604. Next, the system determines anidentity of a user performing the search at 606, and determines currentpricing of the items to be displayed based on the user identity andother parameters at 608. The other parameters at 608 include, forexample:

1. User loyalty (based on shopping behavior, such as past orders on aweb site).

2. User device (such as a mobile device and a corresponding proximity toa physical retail store).

3. User returns (such as a number of times the user has returnedpreviously purchased items).

4. User interests (which category of items a user views and shops moston web site, in stores or using kiosks).

Finally, the system generates a search listing with associated pricinginformation in response to the query at 610. This search listing may bepresented to a user, stored for later retrieval or communicated toanother system for device for processing.

FIG. 7 is a flow diagram depicting an embodiment of a dynamic pricingalgorithm 700, referred to as the weighted seed algorithm. The followingvariables and parameters are associated with this algorithm.

SEED: A Seed is identified as a distinct event or combination ofdistinct events that can be added dynamically as an event adapter to theevent cloud 102. It consists of a numeric identifier and a characterevent name.

SEEDVALUEFACTOR: The change in value of the SEED for the correspondingStock Keeping Unit (SKU) divided by a numeric factor. For example,Inventory Changes has a factor of 100 while Profit has a factor of 1.

ASSIGNED WEIGHT: The weight defines the factor for particular SEED toaffect the price of an item. Higher the seed weight greater the variancein the price changes for SEEDVALUE changes. This is the initial assignedweight to the SEED by the merchandiser.

ACTUAL WEIGHT: Based on trend analyzer 108, the weight changesdynamically. It allows for better pricing changes based on order/demandtrends. This is the weight factor considered for every subsequent event.

SEEDTYPE: STATIC or DYNAMIC. Static Seed weights are constant and can bechanged by the merchandiser through a graphical user interface (GUI).Dynamic Seed weights can be changed by trend analyzer 108 based on ordertrends.

SEEDEFFECT: This is the effect the SEED has on pricing. It can have aPOSITIVE effect or a NEGATIVE effect. A POSTIVE effect decreases theprice whereas a NEGATIVE effect increases the price. For example,positive inventory changes, such as inventory additions, are a POSTIVESEED type and PROFIT is a NEGATIVE seed type. This allows for changes toprice without sacrificing profit.

PRICERANGEPERCENTAGE: This is +/−percent based on the item value definedby merchandiser. For example, price range % of 5, will restrict theprice changes to +/−5% of the merchandiser price.

As seen in FIG. 7, a dynamic pricing algorithm 700 initially determineswhether an event is valid at 702. If the event is not valid, the dynamicpricing algorithm 700 discards the event at 706. If the event is valid,the seed value associated with the event is saved at 704. The dynamicpricing algorithm 700 then gets the seed weight, assigned weight, actualweight and the seed type at 708. The next step in the dynamic pricingalgorithm 700 determines whether the actual weight is present at 710. Ifthe actual weight is not present, the dynamic pricing algorithm 700 usesthe assigned weight only, and replaces the assigned weight by the actualweight at 712. If the actual weight is present, the dynamic pricingalgorithm 700 uses the actual weight only at 714. Next, the dynamicpricing algorithm 700 decides whether all seed values are present at716. If all the seed values are not present, the dynamic pricingalgorithm 700 redistributes weight across other available seeds with sumtotal of all weights as 1 at 718, and then proceeds to compute the pricebased on the formula at 722:

Price=.SIGMA.SeedWeight.times.SeedValueFactor.times.Weight.times.SeedType

If the dynamic pricing algorithm 700 determines that all seeds arepresent, the algorithm directly computes the price based on the formulaat 722. The dynamic pricing algorithm 700 then checks the percentagerange at 724. If the percentage range is lower than the minimum price,the dynamic pricing algorithm 700 increases the weight of the negativeseeds and decreases the weight of the positive seeds with sum total ofweights as 1 at 720, and then re-computes the price at 722. If thepercentage range is higher than the minimum price, the dynamic pricingalgorithm 700 decreases the weight of the negative seeds and increasesthe weight of the positive seeds with sum total of weights as 1 at 726,and then re-computes the price at 722. If the percentage range is inrange at 724, the price is published to the orchestrator and analyzer at728. The analyzer compares historical order versus trends on a periodicbasis at 730. Based on an increase or decrease on orders, the dynamicpricing algorithm 700 changes the weights of dynamic seed types with asum total of all weights as 1 at 732. The dynamic pricing algorithm 700then returns to get the seed weight, assigned weight, actual weight andseed type at 708, and the process repeats.

FIG. 8 shows a list of five example seed variables. As seen in thefigure, the seed AVGPROFIT (average profit) is defined as static andnegative. In some embodiments, only the merchandiser can change theseeded weight and it has a negative effect on price decrease. All otherseeds shown in FIG. 8 have a positive effect on price decrease and theirseeded weight can be changed by trend analyzer 108.

FIG. 9 shows an example listing of how seeds are associated with items(SKU) and item category (SKU category). As seen in the FIG. 9, the SKUcategory of Electronics can have a price change range of +/−10% of themerchandiser price. The event orchestrator 106 feeds different seedvalues (factored) to item SKUID WMT3456. A seed value of zero or nullindicates the associated seed weight is not applied. If a seed weight isnot applied, the weight of that seed is distributed across otheravailable seeds. In the example below, the weight of order change isdistributed across the other three available seeds for item WMT1023. Theprice range percentage is on category level/SKU level to restrict theprice changes on a macro (category) or a micro (item) view.

Although the present disclosure is described in terms of certain exampleembodiments, other embodiments will be apparent to those of ordinaryskill in the art, given the benefit of this disclosure, includingembodiments that do not provide all of the benefits and features setforth herein, which are also within the scope of this disclosure. It isto be understood that other embodiments may be utilized, withoutdeparting from the scope of the present disclosure.

What is claimed is:
 1. A dynamic pricing system comprising: one or moreprocessors; and memory storing one or more programs to be executed bythe one or more processors, the one or more programs comprisinginstructions for: receive a request from a graphical user interface of amobile device of a user for a price of one or more items; receive anindication of an occurrence of a first event unrelated to a particularcustomer, wherein the first event is related to the one or more items;receive an indication of an occurrence of a second event unrelated to aparticular customer, wherein the second event is related to the one ormore items; access data regarding the first event and the second event;determine whether to adjust the price associated with the one or moreitems based on the data regarding the first event and the second event;responsive to determining to adjust the price associated with the one ormore items, determine a new price for the one or more items based on thefirst event, the second event, and previous user behavior comprising atleast one of user loyalty, user returns, or user interests of the user;generate a search listing comprising the one or more items responsive tothe request of the user based on the price, as adjusted, of the one ormore items in the search listing; when it is determined that a priceadjustment is not required for the one or more items, displaying theprice without adjustment of the one or more items in response to therequest of the user; and facilitating displaying, to the graphical userinterface of the mobile device, the final search listing in response tothe request of the user.
 2. The dynamic pricing system of claim 1,further comprising: determining whether the first event or the secondevent is a valid event based on a dynamic pricing algorithm, whereinwhen the first event or the second event is determined not to be valid,the invalid first event or second event is discarded.
 3. The dynamicpricing system of claim 1, wherein the first event comprises at leastone of: a browsing history; a social media post; an inventory change; ashipping cost change; a competitor price change; a plurality of neworders placed for a particular item; a plurality of new orders placedfor items related to the particular item; a promotional event; aproximity of a user to a physical retail store; or a vendor supplychange.
 4. The dynamic pricing system of claim 1, further comprisingassociating the new price with a particular item of the one or moreitems.
 5. The dynamic pricing system of claim 4, further comprisingstoring the new price for the particular item of the one or more itemsfor presentation to a plurality of users.
 6. The dynamic pricing systemof claim 1, wherein the new price is determined based at least on anidentified range of acceptable prices for the one or more items.
 7. Thedynamic pricing system of claim 1, wherein the identified range ofacceptable prices is determined by a vendor of the one or more items. 8.The dynamic pricing system of claim 1, wherein determining the new pricefor the one or more items is independent of competitor price variations.9. The dynamic pricing system of claim 1, further comprising:determining a proximity of the user to a physical retail store; and whenthe user is within a predetermined distance of the physical store,communicating a discount coupon for the one or more items to the mobiledevice of the user based on the first event and the second event. 10.The dynamic pricing system of claim 1, wherein generating the searchlisting further comprises storing the search listing for future requestsby the user or other users.
 11. A method comprising: receiving, with acomputer system using one or more processors, a request from a graphicaluser interface of a mobile device of a user for a price of one or moreitems; receiving, with the computer system, an indication of anoccurrence of a first event unrelated to a particular customer, whereinthe first event is related to the one or more items; receiving, with thecomputer system, an indication of an occurrence of a second eventunrelated to a particular customer, wherein the second event is relatedto the one or more items; accessing, with the computer system, dataregarding the first event and the second event; determining, with thecomputer system, whether to adjust the price associated with the one ormore items based on the data regarding the first event and the secondevent; responsive to determining to adjust the price associated with theone or more items, determining, with the computer system, a new pricefor the one or more items based on the first event, the second event,and previous user behavior comprising at least one of user loyalty, userreturns, or user interests of the user; generating, by the computersystem, a search listing comprising the one or more items responsive tothe request of the user based on the price, as adjusted, of the one ormore items in the search listing; when it is determined that a priceadjustment is not required for the one or more items, displaying, by thecomputer system, the price without adjustment of the one or more itemsin response to the request of the user; and facilitating displaying, bythe computer system, to the graphical user interface of the mobiledevice, the final search listing in response to the request of the user.12. The method of claim 11, further comprising: determining, with thecomputer system, whether the first event or the second event is a validevent based on a dynamic pricing algorithm, wherein when the first eventor the second event is determined not to be valid, the invalid firstevent or second event is discarded.
 13. The method of claim 11, whereinthe first event comprises at least one of: a browsing history; a socialmedia post; an inventory change; a shipping cost change; a competitorprice change; a plurality of new orders placed for a particular item; aplurality of new orders placed for items related to the particular item;a promotional event; a proximity of the user to a physical retail store;or a vendor supply change.
 14. The method of claim 11, furthercomprising, with the computer system, associating the new price with aparticular item of the one or more items.
 15. The method of claim 14,further comprising storing the new price for the particular item of theone or more items for presentation to a plurality of users.
 16. Themethod of claim 11, wherein determining the new item price comprisesidentifying a range of acceptable prices for the one or more items. 17.The method of claim 11, wherein the range of acceptable prices isdetermined by a vendor of the one or more items.
 18. The method of claim11, wherein determining the new price for the one or more items isindependent of competitor price variations.
 19. The method of claim 11,further comprising: determining, with the computer system, a proximityof the user to a physical retail store; and when the user is within apredetermined distance of the physical store, communicating a discountcoupon of the one or more items to the mobile device of the user basedon the first event and the second event.
 20. The method of claim 11,wherein generating, with the computer system, the search listing furthercomprises storing the search listing for future requests by the user orother users.